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TIP
2010
255views more  TIP 2010»
13 years 2 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
CORR
2010
Springer
139views Education» more  CORR 2010»
13 years 2 months ago
On Communication over Unknown Sparse Frequency-Selective Block-Fading Channels
The problem of reliable communication over unknown frequency-selective block-fading channels with sparse impulse responses is considered. In particular, discrete-time impulse respo...
Arun Pachai Kannu, Philip Schniter
SDM
2012
SIAM
322views Data Mining» more  SDM 2012»
11 years 9 months ago
Adaptive Multi-task Sparse Learning with an Application to fMRI Study
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...
ICIW
2009
IEEE
14 years 2 months ago
Paircoding: Improving File Sharing Using Sparse Network Codes
BitTorrent and Practical Network Coding are efficient methods for sharing files in a peer-to-peer network. Both face the problem to distribute a given file using peers with dif...
Christian Ortolf, Christian Schindelhauer, Arne Va...
IJCNN
2007
IEEE
14 years 1 months ago
Probability Density Function Estimation Using Orthogonal Forward Regression
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
Sheng Chen, Xia Hong, Chris J. Harris